Spaces:
Configuration error
Configuration error
File size: 1,241 Bytes
4efbc62 |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 |
# EfficientViT: Multi-Scale Linear Attention for High-Resolution Dense Prediction
# Han Cai, Junyan Li, Muyan Hu, Chuang Gan, Song Han
# International Conference on Computer Vision (ICCV), 2023
import torch
from efficientvit.apps.utils.dist import sync_tensor
__all__ = ["AverageMeter"]
class AverageMeter:
"""Computes and stores the average and current value."""
def __init__(self, is_distributed=True):
self.is_distributed = is_distributed
self.sum = 0
self.count = 0
def _sync(self, val: torch.Tensor or int or float) -> torch.Tensor or int or float:
return sync_tensor(val, reduce="sum") if self.is_distributed else val
def update(self, val: torch.Tensor or int or float, delta_n=1):
self.count += self._sync(delta_n)
self.sum += self._sync(val * delta_n)
def get_count(self) -> torch.Tensor or int or float:
return (
self.count.item()
if isinstance(self.count, torch.Tensor) and self.count.numel() == 1
else self.count
)
@property
def avg(self):
avg = -1 if self.count == 0 else self.sum / self.count
return avg.item() if isinstance(avg, torch.Tensor) and avg.numel() == 1 else avg
|